Flare vs Sunburst: Which GPT Image 2.5 Model Should You Use?

On Image 2, GPT Image 2.5 ships as two routes: Flare and Sunburst. Both share credits, aspect ratios, and reference uploads. The difference is what you optimize for—speed and everyday quality, or tighter multi-turn edit control.

Quick answer

• Choose Flare when you need fast, high-quality defaults: social posts, product frames, moodboards, and high-volume iteration.
• Choose Sunburst when a piece must survive several precise edits—campaign heroes, packaging comps, or “change only the copy” jobs.
• Keep GPT Image 2 when a simple brief already works and you do not need the newer fidelity/speed gains.

What Flare is good at

Flare is the everyday GPT Image 2.5 default. Relative to GPT Image 2 it usually feels sharper and more responsive, which helps when you are exploring layouts instead of polishing one final frame.

Use Flare when:

• You generate many variations in a session
• The brief is clear (subject + scene + lighting) and you do not need surgical local edits
• Latency matters more than maximum edit precision

What Sunburst is good at

Sunburst targets premium creative workflows. Generation can take longer, but multi-turn instructions hold better—so earlier constraints are less likely to drift when you refine.

Use Sunburst when:

• You will edit the same image across several turns
• Brand identity or product detail must stay locked while one element changes
• You are finishing a hero asset, not brainstorming

A simple decision rule

1. Start on Flare with the same prompt and references.
2. If the first result is close but local edits keep shifting the whole frame, switch to Sunburst.
3. Prefer one change per edit turn on Sunburst (text, product, or background—not all three).

Same Image 2 workflow either way

Open the generator, write or load a prompt, optionally add references, then pick the model. Credits are transparent before you click generate. For a fuller Images 2.5 overview, see GPT Image 2.5 on Image 2 or the GPT Image 2.5 landing page.

The goal is a short loop: inspire, generate, refine, save—with the right 2.5 route for the job.